Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia.
Department of Computing & Games, School of Computing, Engineering & Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK.
Sensors (Basel). 2022 Apr 26;22(9):3331. doi: 10.3390/s22093331.
An electroencephalography (EEG)-based brain-computer interface (BCI) is a system that provides a pathway between the brain and external devices by interpreting EEG. EEG-based BCI applications have initially been developed for medical purposes, with the aim of facilitating the return of patients to normal life. In addition to the initial aim, EEG-based BCI applications have also gained increasing significance in the non-medical domain, improving the life of healthy people, for instance, by making it more efficient, collaborative and helping develop themselves. The objective of this review is to give a systematic overview of the literature on EEG-based BCI applications from the period of 2009 until 2019. The systematic literature review has been prepared based on three databases PubMed, Web of Science and Scopus. This review was conducted following the PRISMA model. In this review, 202 publications were selected based on specific eligibility criteria. The distribution of the research between the medical and non-medical domain has been analyzed and further categorized into fields of research within the reviewed domains. In this review, the equipment used for gathering EEG data and signal processing methods have also been reviewed. Additionally, current challenges in the field and possibilities for the future have been analyzed.
基于脑电图(EEG)的脑机接口(BCI)是一种通过解释 EEG 为大脑和外部设备之间提供通路的系统。基于 EEG 的 BCI 应用最初是为医疗目的开发的,旨在帮助患者恢复正常生活。除了最初的目标,基于 EEG 的 BCI 应用在非医疗领域也越来越重要,例如,通过提高效率、协作和帮助自我发展,改善健康人的生活。本综述的目的是对 2009 年至 2019 年期间基于 EEG 的 BCI 应用的文献进行系统综述。系统文献综述是基于 PubMed、Web of Science 和 Scopus 三个数据库准备的。本综述遵循 PRISMA 模型进行。在本次综述中,根据特定的入选标准,选择了 202 篇出版物。分析了研究在医学和非医学领域的分布,并进一步分为所审查领域的研究领域。在本次综述中,还对用于收集 EEG 数据的设备和信号处理方法进行了回顾。此外,还分析了当前领域的挑战和未来的可能性。